Screenshots of legitimate emails and phishing emails. The dataset likely contains visual representations of email content for classification tasks. The author, organization, and temporal coverage are unknown.
Use Cases
- Train image-based phishing detection models based on screenshot content.
- Compare visual layouts of phishing versus legitimate emails.
- Benchmark computer vision algorithms for security applications.
Strengths
- Focuses on a specific security threat (phishing).
- Provides a visual representation of email data.
Limitations
- Description metadata is limited; actual data quality requires manual inspection after download.
- Row count is unknown, which may limit suitability assessment.
- Column-level documentation is absent; field semantics must be inferred after download.